cjratcliff / variational-dropoutLinks
TensorFlow implementation of the method from Variational Dropout Sparsifies Deep Neural Networks, Molchanov et al. (2017)
☆16Updated 8 years ago
Alternatives and similar repositories for variational-dropout
Users that are interested in variational-dropout are comparing it to the libraries listed below
Sorting:
- Replication of the paper "Variational Dropout and the Local Reparameterization Trick" using Lasagne.☆33Updated 7 years ago
- boundary-seeking generative adversarial networks☆46Updated 7 years ago
- Implementation of paper "GibbsNet: Iterative Adversarial Inference for Deep Graphical Models" in PyTorch☆57Updated 7 years ago
- Example implementation of the Bayesian neural network in "Structured and Efficient Variational Deep Learning with Matrix Gaussian Posteri…☆30Updated 5 years ago
- Deep variational inference in tensorflow☆57Updated 7 years ago
- Code for "Deep Convolutional Networks as shallow Gaussian Processes"☆39Updated 6 years ago
- Implementation of auxiliary deep generative models for semi-supervised learning☆28Updated 9 years ago
- Code for the paper "Improving Variational Auto-Encoders using Householder Flow" (https://arxiv.org/abs/1611.09630)☆75Updated 8 years ago
- Contains code relating to this arxiv paper https://arxiv.org/abs/1802.03761☆37Updated 7 years ago
- Multiplicative Normalizing Flow (MNF) posteriors for variational Bayesian neural networks☆65Updated 5 years ago
- A Lasagne and Theano implementation of the paper Alireza Makhzani, Jonathon Shlens, Navdeep Jaitly, and Ian Goodfellow.☆41Updated 9 years ago
- Code for paper "Full-Capacity Unitary Recurrent Neural Networks"☆54Updated 8 years ago
- A pytorch implementation of "Self-Normalizing Neural Networks" by Klambauer et al. (still beta)☆60Updated 8 years ago
- Professor Forcing, NIPS'16☆45Updated 8 years ago
- Code release for the paper "Calibrating Energy-based Generative Adversarial Networks"☆24Updated 7 years ago
- ☆26Updated 6 years ago
- Implementation of "Variational Inference for Monte Carlo Objectives"☆21Updated 5 years ago
- numpy implementation of net 2 net from the paper Net2Net: Accelerating Learning via Knowledge Transfer http://arxiv.org/abs/1511.05641☆53Updated 9 years ago
- An iterative neural autoregressive distribution estimator (NADE-K)☆26Updated 10 years ago
- Understanding Short-Horizon Bias in Stochastic Meta-Optimization☆37Updated 7 years ago
- An implementation of a Variational-Autoencoder using the Gumbel-Softmax reparametrization trick in TensorFlow (tested on r1.5 CPU and GPU…☆72Updated 7 years ago
- TensorFlow implementation of (Momentum) Stochastic Variance-Adapted Gradient.☆44Updated 7 years ago
- Implementation of Coulomb GANs☆62Updated 4 years ago
- MADE: Masked Autoencoder for Distribution Estimation☆103Updated 5 years ago
- ☆16Updated 8 years ago
- Weight initialization schemes for PyTorch nn.Modules☆70Updated 8 years ago
- ☆29Updated 8 years ago
- Code for the paper Implicit Weight Uncertainty in Neural Networks☆65Updated 5 years ago
- Code for "How to Train Deep Variational Autoencoders and Probabilistic Ladder Networks"☆103Updated 9 years ago
- Python package to sample from determinantal point processes☆18Updated 10 years ago